similar to: r syntax

Dear people, I have got a question concerning the underlying numerical codes when reading an SPSS file into R. I used the package foreign and when I look at a variable I get the verbal codes. I would like to know how it is possible to get the underlying numerical codes as output, which are the same as in my SPSS file. Thank you very much in advance for your help! Marion [[alternative HTML

Hi R-helpers, I am trying to use this ifelse statement to recode a variable: > data$SOCIAL_STATUS<-ifelse(data$SOCIAL_STATUS=="B" & data$MALE>4, "C", "B") (i.e., if social status is B and there are more than 4 males, then recode social status to C; otherwise, leave it B) But, it's not working. See the below R output. Notice that there were 71

Buenas noches, mi pregunta es tal vez sencilla. tengo esta libreria y estos datos library(nlme) data(MathAchieve) Infoest = MathAchieve en esta base quiero contar la cantidad de casos en la que la columna Sex, toma el valor Female, como puedo hacerle el filtro para ver solo los Females. y como puedo dentro del mismo conjunto de datos agregar la variable numerica que me cuente 1 si es Female y 0

Hmm, the danger in this is that duplicated factor levels _used_ to be allowed (i.e. multiple codes with the same level). Disallowing it is what broke read.spss() on some files, because SPSS's concept of value labels is not 1-to-1 with factors. Reallowing it with different semantics could be premature. I mean, if we hadn't had the "forbidden" step, read.spss() could have changed

Hi A.K Regarding my question on comparing normal/ obese/overweight with blood pressure change, I did finally as per the first suggestion of stacking the data and creating a normal category . This only gives me a obese not obese 14, but when I did with the wide format hoping to get a obese14,normal14,overweight 14 Vs hibp 21, i could not complete any of the models. This time I classified obese=1

To extwnd on Martin 's explanation : In factor(), levels are the unique input values and labels the unique output values. So the function levels() actually displays the labels. Cheers Joris On 15 Jun 2017 17:15, "Martin Maechler" <maechler at stat.math.ethz.ch> wrote: >>>>> Paul Johnson <pauljohn32 at gmail.com> >>>>> on Wed, 14 Jun

I currently have a data set in which gender is inputed as "Male" and "Female" , and I'm trying to convert this into "1" and "0". I found a website which reccomended using two commands: data$scode[data$sex=="M"] <- "1" data$scode[data$sex=="F"] <- "2" to convert to numbers, and: data$scode <-

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Hello! I have a dataset with variables in string format (ages class and sex) which I want to recode as numerical variables. How can I accomplish this? Is there any way to do that automatically? Could someone help me? Thanks in advance, Marcos -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

Hi, I have a column in a data frame looking something like: $sex $language $count male english 0 male english 0 female english 32 male spanish 154 female english 11 female norweigan 7 and so on. What I want to do is to order these in to categories, for instance one category where count>=0 & count<10 and so on.. I want my data to turn out looking something like: male

Hi All, I have the data like this : >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

Dear list, I have following data set, which I want to plot the "Scale" variable on the x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The Mean value of each Ageclass for each sex would be connected by a line. Totally, there should be 6 lines, from which three present the Mean values of each Ageclass for respective sex. Are there any easy ways to do

Hello R-users/experts, I am new to R- I have a simple question: Let say I have a data set as follows temp:[file attached] the data structure is a follows: sex age female 28 female 53 female 53 female 36 male 42 male 29 male 43 male 36 male 41 Here we are grouping all male value into male and all female value in to female

I'm trying to remove the elements "No" from the character vector

Hi all, I have data like this: >sample <- read.csv(file="sample.csv",sep=",",header=TRUE) > sample stdate Domain sex age Login 1 01/11/09 xxx FeMale 25 2 2 01/11/09 xxx FeMale 35 4 3 01/11/09 xxx Male 18 30 4 01/11/09 xxx Male 31 3 5 02/11/09 xxx Male 32 11 6 02/11/09 xxx Male 31 1 7 02/11/09

Hi, I have a data set similar to the following State Gender Quantity TX Male 1 NY Female 2 TX Male 3 NY Female 4 I need to calculate cumulative sum of the quantity by State and Gender. The expected output is State Gender Quantity CumQuantity TX Male 1 1 TX Male 3 4 NY Female 2 2 NY Female 4 6 I highly appreciate if someone can give me some hints on solving that in R. Hao -- View this

Hi, I have newbie question. Suppose I have the following data: temp <- data.frame(type1 = c("male", "female", "male", "female", "female"), type2 = c("low", "med", "high", "low", "med"), a = c(1,2,4, NA, 3), b = .... [TRUNCATED] temp type1 type2 a b c 1 male low 1 5 0 2 female

Hey, Is it possible that R can calculate each options under each column and return a summary table? Suppose I have a table like this: Gender Age Rate Female 0-10 Good Male 0-10 Good Female 11-20 Bad Male 11-20 Bad Male >20 N/A I want to have a summary table including the information that how many answers in each category, sth like this: X

I am trying to add confidence (error) bars to lattice barcharts (and dotplots, and xyplots). I found this helpful message from Deepayan Sarkar and based teh code below on it: http://finzi.psych.upenn.edu/R/Rhelp02a/archive/50299.html However, I can't get it to work with groups, as illustrated. I am sure I am missing something elementary, but I am unsure what. Using R 2.1.1 on various